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A Downsampled Variant of ImageNet as an Alternative to the CIFAR
  datasets

A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets

27 July 2017
P. Chrabaszcz
I. Loshchilov
Frank Hutter
    SSeg
    OOD
ArXivPDFHTML

Papers citing "A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets"

31 / 131 papers shown
Title
Learning Rates as a Function of Batch Size: A Random Matrix Theory
  Approach to Neural Network Training
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training
Diego Granziol
S. Zohren
Stephen J. Roberts
ODL
37
48
0
16 Jun 2020
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Sheheryar Zaidi
Arber Zela
T. Elsken
Chris Holmes
Frank Hutter
Yee Whye Teh
OOD
UQCV
18
71
0
15 Jun 2020
Multi-fidelity Neural Architecture Search with Knowledge Distillation
Multi-fidelity Neural Architecture Search with Knowledge Distillation
I. Trofimov
Nikita Klyuchnikov
Mikhail Salnikov
Alexander N. Filippov
Evgeny Burnaev
32
15
0
15 Jun 2020
PatchUp: A Feature-Space Block-Level Regularization Technique for
  Convolutional Neural Networks
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks
Mojtaba Faramarzi
Mohammad Amini
Akilesh Badrinaaraayanan
Vikas Verma
A. Chandar
AAML
26
31
0
14 Jun 2020
Does Unsupervised Architecture Representation Learning Help Neural
  Architecture Search?
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
Shen Yan
Yu Zheng
Wei Ao
Xiao Zeng
Mi Zhang
SSL
AI4CE
30
99
0
12 Jun 2020
An Introduction to Neural Architecture Search for Convolutional Networks
An Introduction to Neural Architecture Search for Convolutional Networks
George Kyriakides
K. Margaritis
AI4CE
23
27
0
22 May 2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real
Chen Liang
David R. So
Quoc V. Le
39
220
0
06 Mar 2020
Iterative Averaging in the Quest for Best Test Error
Iterative Averaging in the Quest for Best Test Error
Diego Granziol
Xingchen Wan
Samuel Albanie
Stephen J. Roberts
10
3
0
02 Mar 2020
Learning When and Where to Zoom with Deep Reinforcement Learning
Learning When and Where to Zoom with Deep Reinforcement Learning
Burak Uzkent
Stefano Ermon
27
66
0
01 Mar 2020
Neural Data Server: A Large-Scale Search Engine for Transfer Learning
  Data
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data
Xi Yan
David Acuna
Sanja Fidler
24
42
0
09 Jan 2020
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture
  Search
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search
Xuanyi Dong
Yi Yang
41
695
0
02 Jan 2020
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas
Yuxuan Zhang
Florian Kerschbaum
MLAU
FedML
AAML
31
144
0
02 Dec 2019
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems
  With Limited Data
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data
Xinyun Chen
Wenxiao Wang
Chris Bender
Yiming Ding
R. Jia
Bo-wen Li
D. Song
AAML
19
106
0
17 Nov 2019
Robust Training with Ensemble Consensus
Robust Training with Ensemble Consensus
Jisoo Lee
Sae-Young Chung
NoLa
19
28
0
22 Oct 2019
ReNAS:Relativistic Evaluation of Neural Architecture Search
ReNAS:Relativistic Evaluation of Neural Architecture Search
Yixing Xu
Yunhe Wang
Avishkar Bhoopchand
Christopher Mattern
A. Grabska-Barwinska
Chunjing Xu
Chang Xu
22
81
0
30 Sep 2019
AutoGAN: Neural Architecture Search for Generative Adversarial Networks
AutoGAN: Neural Architecture Search for Generative Adversarial Networks
Xinyu Gong
Shiyu Chang
Yi Ding
Zhangyang Wang
GAN
35
263
0
11 Aug 2019
AutoML: A Survey of the State-of-the-Art
AutoML: A Survey of the State-of-the-Art
Xin He
Kaiyong Zhao
X. Chu
20
1,419
0
02 Aug 2019
A framework for the extraction of Deep Neural Networks by leveraging
  public data
A framework for the extraction of Deep Neural Networks by leveraging public data
Soham Pal
Yash Gupta
Aditya Shukla
Aditya Kanade
S. Shevade
V. Ganapathy
FedML
MLAU
MIACV
27
56
0
22 May 2019
Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild
Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild
Kibok Lee
Kimin Lee
Jinwoo Shin
Honglak Lee
CLL
29
201
0
29 Mar 2019
Class-incremental Learning via Deep Model Consolidation
Class-incremental Learning via Deep Model Consolidation
Junting Zhang
Jie Zhang
Shalini Ghosh
Dawei Li
Serafettin Tasci
Larry Heck
Heming Zhang
C.-C. Jay Kuo
CLL
13
333
0
19 Mar 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Kimin Lee
Mantas Mazeika
NoLa
17
717
0
28 Jan 2019
Deep Anomaly Detection with Outlier Exposure
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks
Mantas Mazeika
Thomas G. Dietterich
OODD
31
1,449
0
11 Dec 2018
Controlling Over-generalization and its Effect on Adversarial Examples
  Generation and Detection
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection
Mahdieh Abbasi
Arezoo Rajabi
A. Mozafari
R. Bobba
Christian Gagné
AAML
16
9
0
21 Aug 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and
  Adversarial Attacks
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
OODD
21
1,994
0
10 Jul 2018
Laplacian Networks: Bounding Indicator Function Smoothness for Neural
  Network Robustness
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness
Carlos Lassance
Vincent Gripon
Antonio Ortega
AAML
24
16
0
24 May 2018
Knowledge Distillation with Adversarial Samples Supporting Decision
  Boundary
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Byeongho Heo
Minsik Lee
Sangdoo Yun
J. Choi
AAML
21
146
0
15 May 2018
Efficient Multi-objective Neural Architecture Search via Lamarckian
  Evolution
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution
T. Elsken
J. H. Metzen
Frank Hutter
131
498
0
24 Apr 2018
TBD: Benchmarking and Analyzing Deep Neural Network Training
TBD: Benchmarking and Analyzing Deep Neural Network Training
Hongyu Zhu
Mohamed Akrout
Bojian Zheng
Andrew Pelegris
Amar Phanishayee
Bianca Schroeder
Gennady Pekhimenko
23
80
0
16 Mar 2018
Training wide residual networks for deployment using a single bit for
  each weight
Training wide residual networks for deployment using a single bit for each weight
Mark D Mcdonnell
MQ
27
71
0
23 Feb 2018
Decoupled Weight Decay Regularization
Decoupled Weight Decay Regularization
I. Loshchilov
Frank Hutter
OffRL
36
2,078
0
14 Nov 2017
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
233
2,547
0
25 Jan 2016
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